MATLAB & Simulink
DATA ANALYSIS AND MACHINE LEARNING
MATLAB for Data Processing and Visualization
This one-day course focuses on importing and preparing data for data analytics applications. The course is intended for data analysts and data scientists who need to automate the processing, analysis, and visualization of data from multiple sources. Topics include:
Working with irregular data
The aim of this course is to equip those who need to process mixture data types from arbitrarily formatted text data and irregular data and to customized visualization of the data.
Who Should Attend
Techsource Systems is
Mathworks Sole and Authorised Distributor and Training Partner
Engineer, researchers, data scientists, and managers, who are involved in the process of preprocessing of the mixture data types measurement data and irregular data and to create customized.
Upon the completion of the course, the participants will be able to work with text files with arbitrary formatting and work with graphic object properties to customize the plots.
Day 1 of 1
Objective: Read text files that contain a mixture of data types, delimiters, and headers.
Import a mixture of data types from arbitrarily formatted text files
Import only required columns of data from a text file
Import and merge data from multiple files
Objective: Process raw imported data by extracting, manipulating, aggregating, and counting portions of data.
Process data with missing elements
Create and modify categorical arrays
Aggregate, bin, and count groups of data
Objective: Annotate and modify standard plots to produce informative customized graphics.
Determine properties of graphics objects and their associated values
Locate and manipulate graphics objects
Customize plots by modifying properties of graphics objects
Working with Irregular Data
Objective: Import and visualize scattered data from text files with irregular formatting.
Parse text files to determine formatting
Import data from separate sections of a text file
Extract data from container variables
Interpolate irregularly spaced three-dimensional data
Visualize three-dimensional data in two and three dimensions